Customer Analytics For Dummies (2015)
Part III
Analytics for the Customer Journey
Chapter 11
Tracking Post-Purchase Behavior
In This Chapter
Solving cognitive dissonance
Looking at post-purchase touchpoints
Discovering problems with cause-and-effect diagrams
You probably think that once a potential customer becomes an actual customer, your job is done. Not so fast! You may have put a lot of effort into getting that customer to make a purchase, but it’s just as important to put additional effort into turning that customer into a repeat and loyal customer. Not only can that customer make additional purchases from you, but he or she also just might recommend your business, which could lead to even more customers.
As soon as the transaction is complete, customers move into a phase in which you provide service, support, and fulfilling the promises made during the pre-purchase process. This phase of the customer journey can be one of the longest, especially for products or services that aren’t purchased frequently. During this phase, customers can move toward being loyal or less loyal, reconsider the competition, and even be negative influencers. This can lead to an improvement in the perception of the brand or its degradation. This outcome of the post-purchase phase will influence the next purchase consideration for the current customer and for other potential customers as they become influenced by positive and negative word of mouth in person or on social media.
In the post-purchase phase, you continue to measure customers’ attitudes, especially customer satisfaction, brand and product loyalty, and future intent.
In this chapter, I use many of the measures introduced in Chapter 9. The same techniques you use in the pre-purchase phase and consideration phases work in the post-purchase phase, too.
Dealing with Cognitive Dissonance
In the post-purchase phase, you either confirm or alter the ideas and beliefs customers have of you from the pre-purchase and consideration phases. The mismatch between customers’ expectations and their actual experience leads to delight or disappointment and cognitive dissonance.
Cognitive dissonance describes the mental discomfort people feel when their actions and beliefs don’t align. In this case, the beliefs or attitudes are that the product was not a good value and didn’t do what they believed — in other words, buyer’s remorse.
Three of the main causes of cognitive dissonance are
· Value: The price or total payment cost isn’t worth what was paid.
· Quality: The product or service doesn’t perform as expected, is missing features, or breaks.
· Better alternatives: Buyer’s remorse is more intense when a customer has rejected a lot of alternative products.
Reducing dissonance
Customers with cognitive dissonance will take actions to reduce it, which can mean returning a product, spreading negative word of mouth, or not purchasing the product again. Look for evidence of cognitive dissonance, and where possible, correct and prevent it so positive emotions are associated with the purchase and brand.
Customers with high cognitive dissonance can do several things.
· Take no action: The consumer gets over her dissonance (but likely remembers for future purchases).
· Cancel or return the product: This results in a lost sale and cost of handling the return.
For service agreements such as software maintenance contracts, mobile phone service, or cable TV, the cancellation of a customer represents a major loss because of the loss of recurring revenue (see Chapter 6 on calculating customer lifetime value). To keep this customer, offer future discounts or more channels to prevent a cancellation, and assuage dissonance.
When customers return a product, you have to track the return rate. See the upcoming section on dealing with returns.
· Purchase another product: Although the sale is made, the relationship with the company and future purchases are in jeopardy.
· Contact customer support or customer service representatives: This costs your company money in terms of time spent listening to the customer and fixing the problem.
How you handle customers through customer service is vitally important. You have the opportunity to turn a dissatisfied customer into a satisfied one, which could lead to a loyal repeat customer.
· Take legal action: Probably the worst outcome, customers feeling like they need to sue to get out of a contract or get their money back.
Turning dissonance into satisfaction
Product warranties, free return policies, free shipping, and free return shipping help reduce the changes for dissonance.
To address customers’ dissonance, each of these reasons can be addressed using the following approaches.
· Offer a better value. Change the price or increase the offerings for the same price.
· Improve quality. Improving quality is easier said than done. Identify the root cause of the quality concern, whether it be features or performance.
One way to diagnose the root causes of problems is a cause-and-effect diagram. Turn to the later section “Finding the Root Cause with Cause-and-Effect Diagrams” for more information.
· Confirm the initial choice. Messaging, in email newsletters, ads, and follow-up calls, reassures customers that they made the right choice and that the purchase does conform to their attitudes and beliefs.
More information about marketing options to reduce cognitive dissonance can be found in Marketing For Dummies, by Alexander Hiam (Wiley).
Tracking return rates
One of the actions customers can take is to return a product. A return guarantee is key to alleviating cognitive dissonance, but it can be expensive to maintain if you suffer a spate of returns.
When a product is returned, it not only represents a lost sale, but increased costs in repackaging (or an unsalable item) and the logistics to handle the returns.
Once a customer returns a product, there isn’t much that can be done for that customer, but you can learn a lot to prevent future returns.
1. Collect the return rates, dates, and details.
2. Look to other clues that can predict the root cause of returns.
3. Predict the return rates based on patterns in the root causes.
For example, I worked with a U.S.-based cellular service provider that carried a number of phones from different manufacturers, including Apple, Samsung, and Motorola. The cellular service provider collected the return rates for each type of phone and then looked into the causes of the returns. One reason for the returns was that customers found certain phones harder to use. The company started collecting usability data on all its phones, then associated that with the return rates. Based on the data, the company stopped selling the phones that lacked a decent usability score. (See Chapter 9 to find out how to use the System Usability Scale, or SUS.)
Measuring the Post-Purchase Touchpoints
The data you collect in the post-purchase phase aids in understanding how well the experience is at each stage and also how to improve the experience for current and future customers. It could be that customers had great first impressions but had a poor service experience. Measuring at different post-purchase touchpoints helps identify opportunities for improvement.
To easily collect data, establish a feedback loop. Problems, frustrations, and improvements are properly channeled back to the product development teams.
One of the quickest ways to identify opportunities for improvement is to ask customers in a post-purchase survey their level of satisfaction with each of the touchpoints.
Keep the surveys short and ask a mix of open- and closed-ended questions. You should include:
· An overall measure of satisfaction about the product or experience, using a rating scale (see Chapter 9)
· More detailed questions about each touchpoint (also using a rating scale)
· Questions about future intent, such as likelihood to recommend or likelihood to repurchase
· Open-ended questions for customers to describe in their own words their feelings (both positive and negative) about the experience and specifically how they’d improve the product
Digging into the post-purchase touchpoints
You can deploy your surveys at different intervals to correspond with a touchpoint. It’s often most efficient, and less of a burden on the customer, if you ask customers to complete only one survey at a key point in the post-purchase process — say, after the customer has used the product for some time.
Some common touchpoints include:
· Shipping and delivery
· Unboxing (opening the product)
· Installation and setup
· Customer support
· Feature usage
· Overall satisfaction
Shipping and delivery
When customers decide to purchase something, they want it right away. For an in-store purchase, this isn’t much of an issue when the item is in stock. For catalog and Internet purchases, the delay of receiving the goods attenuates the impulsiveness of the purchase decisions. Customers set firm expectations about when they expect a product to arrive. Amazon.com’s next-day (and even same-day) shipping helps alleviate the gap in time that otherwise causes cognitive dissonance to fester. Even if you can’t deliver products the next day, you can measure and improve the customer’s expectations.
For example, when looking at the customer satisfaction of the purchasing process with computer manufacturer Lenovo, the promised production and delivery time are paramount.
Unboxing
The experience of removing a product from its package is one of the first physical touchpoints you have to influence the emotional connection a customer has with the brand. For example, the unboxing experience of the iPhone helps reinforce Apple’s branding as being cutting edge, clean, and easy to use; see Figure 11-1.
Figure 11-1: iPhone unboxing experience helps reinforce the brand attributes of a clean, cutting-edge design.
Installation and setup
For many products, after the unboxing experience, the setup and installation process defines the first moments of the post-purchase phase. A lot of customers lose enthusiasm for a product after unsuccessfully trying to get it to work. Asking about the installation and setup experience in your post-purchase surveys helps identify how much this step influences customers’ overall attitudes and future intent. It also helps identify problems that can be addressed.
For example, in the mid-1980s, my friend Jim Lewis was helping the IBM printer division understand the impacts of the setup and installation phase of a new series of IBM printers. They discovered an error in the documentation that could potentially cause a problem in installation. This would lead to product returns, calls to customer support (see the next section), and a poor experience. But reprinting all the manuals to fix the problem would also be costly. So a team of IBM researchers wanted to see if adding a large “Read This First” paper with the correct instructions on top of the printer and original installation instructions would prevent the problem. After asking several customers to open and set up the printer, IBM researchers watched as most of these study participants completely ignored the “Read This First” paper and incorrectly set up the printer. IBM decided to reprint the manuals instead of risking high returns and a failed installation experience.
Customer support
Customer support is one of the most common post-purchase touchpoints. This usually consists of a call center, email support, or online chat feature. In many companies, the sales team is comprised of employees who have the charm and personality to make the sales process smooth. Unfortunately, that isn’t necessarily the same experience the customer encounters when working with the support teams. Call centers and support teams are often outsourced, which may create a language, cultural, or physical distance barrier between the customer and this important company touchpoint.
Customer support is not just an opportunity to satisfy a current customer by addressing a question or complaint; it’s also an opportunity to delight a customer by exceeding her expectations. This leads to more loyal customers.
The customer support touchpoint plays such an important role in post-purchase satisfaction that it often deserves its own (usually short) survey that’s sent immediately after the interaction. Figure 11-2 shows an example customer support survey from Amazon.
If you find that most customers don’t take your post-purchase survey, offer an incentive to do so, such as a discount off a future purchase.
Figure 11-2: A survey invitation sent immediately from Amazon to measure the customer support experience.
Zappos … if the shoe fits (or doesn’t)
Zappos.com is an online store that offers discounted shoes. Buying shoes online comes with some risk since customers can’t try them on and may end up with a pair of shoes they don’t want and the hassle of returning them. Prospective customers naturally want to minimize the chances of buying shoes that don’t fit or that they don’t like (avoiding cognitive dissonance). Zappos minimizes the risk to the customer by offering free returns and free return shipping.
What’s more, Zappos provides one of the best customer service experiences. Zappos customer service reps are known for staying on calls for as long as it takes to resolve a customer’s problems. (The longest call on record lasted seven hours!) The company’s even been known to refund money, let customers keep the shoes, and even send a new pair, all to exceed expectations and keep customers coming back and telling friends about their experience.
Feature usage
It’s often the case that customers will purchase a product for a set of features during the consideration phase, but use only a subset in the post-purchase phase. Collect data about which features of the product customers are actually using and those they are not using. Also ask what features are missing that they would like. (See Chapter 14 for ideas on measuring usability.)
Assessing post-purchase satisfaction ratings
You can create your own customer satisfaction questions, but remember that consumer-advocate organizations often also measure customer satisfaction for a variety of things: products, services, and websites:
· The magazine Consumer Reports publishes customers’ complaints and ratings, including their opinions about repair service, for everything from appliances to electronics to automobiles. This information becomes valuable input for prospective customers in the consideration phase.
· Companies such as JD Power and the American Satisfaction Customer Index provide customer satisfaction rates on a number of products.
· The Amazon product rating system is an often cited reference for customers in the consideration phase.
You can use these published sources of customer satisfaction as a benchmark to your own efforts by seeing how competitors (and your product) compare with similar products.
Finding Problems Using Call Center Analysis
A number of analytics measure the customer call center experience. The point of these analytics shouldn’t just be about finding ways to cut costs or improve your support staff’s efficiency. Although it’s important to control costs, it’s equally important to meet customer expectations, which leads to higher levels of satisfaction and customers who are more likely to recommend and repurchase from you. Your metrics must be meaningful to the customer.
Here are six of the most common call center analytics to track, in addition to the satisfaction:
· Customer satisfaction: As with every post-purchase touchpoint, be sure your customer lets you know how well his expectations were met.
Use a simple rating scale, something like that from Amazon (refer to Figure 11-2).
· Call resolution: Was the reason for the call successfully addressed?
Don’t rely exclusively on the customer support agent to provide this detail. Collect data from the customer, if possible. Many call centers pay attention to the percent of calls resolved, which can incentivize prematurely marking issues as resolved. Look at customer satisfaction along with call resolution to be sure expectations are met and problems are solved. See the nearby sidebar on request closed versus request resolved.
· Hold time: People don’t like to listen to music or hear a recording about how valuable a customer they are while they are on hold. Long waits only increase the frustration of an already undesirable situation. It isn’t an easy thing to fix, but it’s an essential metric to track.
· Call abandonment: Long hold times lead to customers hanging up. These abandoned calls contribute to frustration and a degradation of the brand.
· Reason for call: Have customer support agents describe (using a categorization system or comments field) the reason and resolution for the call. All too often, I’ve worked with call-center data to address spikes in calls only to see data that has little information regarding the reason for the call.
· Call duration: A support call takes customers’ time and call agents’ time. While it’s good to get to a resolution as quickly as possible, be careful that you aren’t incentivizing agents to prematurely end calls. In general, no one likes to feel rushed when dealing with an issue. A rushed call might lead to another call, a return, or disloyal customer.
Customer ticket closed or customer request resolved?
The frontlines of the customer experience are often the customer support channels — phone and email. I had a problem with one of my online bank accounts. After trying several tweaks over a few months, I finally got around to submitting a problem ticket via email. Within 24 hours, I received a response (as promised).
Eight hours later, I was told that this sort of thing happens from time to time and is most likely a temporary issue, and that trying again in a day or so should work. I was then told the ticket was closed. Yikes! The next day, the temporary problem was still there. It was another six months before the “temporary issue” was resolved. So while the ticket was closed and closed quickly (both were positive metrics for the call center), my issue lingered.
Finding the Root Cause with Cause-and-Effect Diagrams
Many problems in the post-purchase phase are often symptoms of other problems:
· Customer complaints
· Returns
· Calls to customer support
· Low customer satisfaction ratings
One tool that is particularly handy at getting to root causes is the aptly named cause-and-effect diagram. It is also called the fishbone for its fishlike skeletal shape. An example is shown in Figure 11-3.
Cause-and-effect diagrams provide a visual display of possible causes of a problem. Most importantly, they remind you that there are usually multiple causes of problems that lead to low customer satisfaction. It would be nice if one reason always explained your complex problems — but that’s rarely the case.
Fishbones are low-tech; you need only a piece of paper or a white board for team settings (no need to save the bones from dinner last night).
Figure 11-3: An example cause-and-effect template (fishbone diagram).
Creating a cause-and-effect diagram
Here’s how to use a cause-and-effect diagram in five steps.
1. Define the problem you want to avoid.
Ideally, you want this statement to be as specific as possible. So if you’re dealing with customer returns, a problem statement would be
“Customer return rates are higher than 10%.”
The problem statement goes at the head of the fish.
2. Brainstorm possible causes for the problem.
For high customer return rates, this would be something like
· Customers are unable to set up the product properly.
· Shipping takes too long or is unclear.
· Customers don’t use the product after opening it.
· The price is too high relative to what customers are getting.
· The product breaks or stops working.
These problems become the bones in the fish. You should think causally (for example, what causes customers to improperly set up the product?).
Don’t just use the fishbone to propose solutions. For each cause, ask “Why does this happen?” In fact, ask “why” as many times as you can (like a 3-year-old child does).
For example:
· Customers are unable to set up the product properly: Why?
· The directions are long and unclear: Why?
· It’s complicated to explain the setup: Why?
· Many features and steps need to be explained: Why?
3. Sort the causes into clusters, remove duplicates, and rearrange the bones of the fish.
In Figure 11-4, I filled in two branches of the fish.
4. Name the main bones something descriptive of the causes.
I used Pricing and Product.
5. Identify areas that need data or investigation.
Some causes are obvious (is there any indication of shipping?), whereas others need data (where are customers making mistakes in the setup?). You should get something that looks like Figure 11-4.
Figure 11-4: A part of a cause-and-effect diagram with reasons for high customer return rates.
Now that the causes are in the fishbone, you’ll likely see connections between the causes. Also use this opportunity to continue asking “why” to get at root causes.
Use the cause-and-effect diagram in all stages of the customer journey to brainstorm root causes for product and service problems. It becomes excellent input for finding design solutions and turning negative thinking into positive user experiences.